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Fingerprint Liveness Detection Using Convolutional Neural Networks
2016
IEEE Transactions on Information Forensics and Security
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For both disaster image retrieval and flood-detection in satellite images, we employ neural networks for end-to-end learning. ...
Specifically, for the first subtask, we exploit Convolutional Networks and Relation Networks while, for the latter, dilated Convolutional Networks were employed. ...
FLOOD-DETECTION (FDSI) For the FDSI task, we employed CNNs with dilated (or a-trous) convolution [4] . ...
doi:10.1109/tifs.2016.2520880
fatcat:ijrgisfk7zh63djo7rze55d7xa
Fingerprint Liveness Detection and Visualization Using Convolutional Neural Networks Feature
Convolutional Neural Networks 특징을 이용한 지문 이미지의 위조여부 판별 및 시각화
2016
Journal of the Korea Institute of Information Security and Cryptology
Convolutional Neural Networks 특징을 이용한 지문 이미지의 위조여부 판별 및 시각화
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After the preprocessing part using fingerprint segmentation, the pretrained CNN model is used for detecting the liveness detection. ...
Not only a liveness detection but also feature analysis about the live fingerprint and fake fingerprint are provided after classifying which materials are used for making the fake fingerprint. ...
Fingerprint image Segmented results using coherence Fig. 3. ...
doi:10.13089/jkiisc.2016.26.5.1259
fatcat:6rksufijqrftbpfjzzsja4wwva
Slim-ResCNN: A deep Residual Convolutional Neural Network for Fingerprint Liveness Detection
2019
IEEE Access
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The convolutional neural networks (CNNs) have shown impressive performance and great potential in advancing the state-of-the-art of fingerprint liveness detection. ...
network for spoof fingerprint detection. ...
Convolutional Neural Networks (CNNs), which have been widely used in computer vision, make outstanding performance in image classification [19] , object detection [20] and many other tasks [21] , attributing ...
doi:10.1109/access.2019.2927357
fatcat:hikutynxbnhrdnajynplibv2xy
fPADnet: Small and Efficient Convolutional Neural Network for Presentation Attack Detection
2018
Sensors
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This paper proposes a presentation attack detection method using Convolutional Neural Networks (CNN), named fPADnet (fingerprint Presentation Attack Detection network), which consists of Fire and Gram-K ...
Combining Fire and Gram-K modules results in a compact and efficient network for fake fingerprint detection. ...
There are two approaches to use convolutional neural networks in fake fingerprint detection. ...
doi:10.3390/s18082532
pmid:30072662
fatcat:jyetjbi4araffjpgs4jgnya6wq
Patch-based Fake Fingerprint Detection Using a Fully Convolutional Neural Network with a Small Number of Parameters and an Optimal Threshold
[article]
2018
arXiv
pre-print
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This study proposes a patch-based fake fingerprint detection method using a fully convolutional neural network with a small number of parameters and an optimal threshold to solve the above-mentioned problem ...
The proposed convolutional neural network (CNN) structure applies the Fire module of SqueezeNet, and the fewer parameters used require only 2.0 MB of memory. ...
The structure of the proposed fully convolutional neural networks with
optimal threshold value for patch based fingerprint liveness detection. ...
arXiv:1803.07817v1
fatcat:cmkkdrvs4va45pc6wihu7y54wq
A Lightweight Convolutional Neural Network with Representation Self-challenge for Fingerprint Liveness Detection
2022
Computers Materials & Continua
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To address challenges from PA, fingerprint liveness detection (FLD) technology has been proposed and gradually attracted people's attention. ...
Aiming at filling this gap, this paper designs a lightweight multi-scale convolutional neural network method, and further proposes a novel hybrid spatial pyramid pooling block to extract abundant features ...
Multi-scale lightweight network. A multi-scale parallel neural network is proposed for the fingerprint liveness detection task. ...
doi:10.32604/cmc.2022.027984
fatcat:mbo2amzshjelvbl5zfzh6h37pe
Implementation of Convolutional Neural Network to Classification Gender based on Fingerprint
2021
International Journal of Modern Education and Computer Science
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Convolutional neural network is one type of deep learning. ...
In this research, will be doing to classification gender based on fingerprint using method Convolutional Neural Network, and then we will make three models to determined gender, with a total of 49270 image ...
using convolutional neural network, and how the accuracy of detecting fingerprint images to determine the gender of someone using convolutional neural network. ...
doi:10.5815/ijmecs.2021.04.05
fatcat:d23gceop6zeyfces7p3w5r7anu
Fingerprint Distortion Detection
2020
International Journal of Scientific Research in Computer Science Engineering and Information Technology
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The approach is to utilize local patches centered and aligned using fingerprint details. ...
Fingerprint is widely used in biometrics, for identification of individual's identity. Biometric recognition is a leading technology for identification and security systems. ...
Fingerprint Liveness Detection Using Convolutional Neural Networks. IEEE Transactions on Information 1213.doi:10.1109/tifs.2016.2520880. [7]. ...
doi:10.32628/cseit2063204
fatcat:mqj5majcjrce7ifnzvs5w5n55m
Fingerprint Liveness Detection using An Improved CNN with Image Scale Equalization
2019
IEEE Access
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Therefore, to ensure that authorized users' fingerprint information is not used illegally, one possible anti-spoofing technique, called fingerprint liveness detection (FLD), has been exploited. ...
INDEX TERMS Fingerprint liveness detection, supervised learning, biometrics, spoof detection, adaptive learning rate. ...
Hereby, to eliminate image scale limitations, in this paper, we propose a novel fingerprint liveness detection method based on an improved convolutional neural network with Image Scale Equalization. ...
doi:10.1109/access.2019.2901235
fatcat:4fmm4ddp6rbo7ljp4srkkfs5ke
Left Or Right Hand Classification From Fingerprint Images Using A Deep Neural Network
2020
Computers Materials & Continua
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In this paper, we designed a deep learning system using deep convolution network to categorize fingerprints as coming from either the left or right hand. ...
In this paper, we applied the Classic CNN (Convolutional Neural Network), AlexNet, Resnet50 (Residual Network), VGG-16, and YOLO (You Only Look Once) networks to this problem, these are deep learning architectures ...
Classification using
Fingerprint
90% acc, Image Processing,
professional knowledge of
fingerprint
Rodrigo
Frasetto
Nogueira
Fingerprint Liveness Detection
95% Acc, Deep Learning,
Livness Detection ...
doi:10.32604/cmc.2020.09044
fatcat:2koudtpy7jgpnch4loeyk3f3mi
A novel pore extraction method for heterogeneous fingerprint images using Convolutional Neural Networks
2017
Pattern Recognition Letters
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Our method uses specifically designed and trained Convolutional Neural Networks (CNN) to estimate and refine the centroid of each pore. ...
In particular, sweat pores can be used for quality assessment, liveness detection, biometric matching in live applications, and matching of partial latent fingerprints in forensic applications. ...
Convolutional Neural Networks Most of the artificial neural networks in the literature (e.g., feedforward neural networks) consist of layers of neurons that process data in the form of one-dimensional ...
doi:10.1016/j.patrec.2017.04.001
fatcat:lk77vzvfx5djblxjrx2ttyhwha
End-to-End Deep Learning Fusion of Fingerprint and Electrocardiogram Signals for Presentation Attack Detection
2020
Sensors
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For the ECG, we investigate three different architectures based on fully-connected layers (FC), a 1D-convolutional neural network (1D-CNN), and a 2D-convolutional neural network (2D-CNN). ...
We also propose a novel end-to-end deep learning-based fusion neural architecture between a fingerprint and an ECG signal to improve PA detection in fingerprint biometrics. ...
Convolutional neural network (CNN) networks have exhibited continuous improvements for spoof detection compared with handcrafted techniques. ...
doi:10.3390/s20072085
pmid:32272813
pmcid:PMC7181006
fatcat:tcsxwsd4kzgfbpwmvv2ygzflca
An Intelligent Approach for Anti-Spoofing in a Multimodal Biometric System
2017
International Journal of Advanced Research in Computer Science and Software Engineering
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The extracted biometric features are fused and fed to a convolution neural network that employs deep learning to detect spoofed features from real features. ...
The proposed method is designed to overcome spoofing in a multimodal biometric system that uses a combination of face, fingerprint and iris images. ...
In Classification, the convolution neural network classifies the output as real or spoof. Step4. ...
doi:10.23956/ijarcsse/v7i3/0143
fatcat:mfyzkngvmzdo7fyscy2qmdxt5y
Contactless Fingerprint Recognition Using Deep Learning—A Systematic Review
2022
Journal of Cybersecurity and Privacy
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Contactless fingerprint identification systems have been introduced to address the deficiencies of contact-based fingerprint systems. ...
A number of studies have been reported regarding contactless fingerprint processing, including classical image processing, the machine-learning pipeline, and a number of deep-learning-based algorithms. ...
In order to recognize contactless fingerprints, this paper [67] described a convolutional neural network (CNN) framework. ...
doi:10.3390/jcp2030036
fatcat:ugz24t4cxffwbomrzl2cyyxq6m
Transformers and Generative Adversarial Networks for Liveness Detection in Multitarget Fingerprint Sensors
2021
Sensors
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In the experiments, we validate the proposed methodology on the public LivDet2015 dataset provided by the liveness detection competition. ...
Fingerprint-based biometric systems have grown rapidly as they are used for various applications including mobile payments, international border security, and financial transactions. ...
[14] proposed a system to generate artificial fingerprints and detect fake fingerprints using deep neural networks. ...
doi:10.3390/s21030699
pmid:33498430
pmcid:PMC7864196
fatcat:jrnzpfdisngejc4epiwyf5sxje
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